The Global Magazine of Leica Geosystems

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20 | Reporter LandBase Level 2 classification over Derby City Center utilising LIDAR height information to further improve classification accuracy. & estuary, inland water, artificial surface, buildings, bare ground, herbaceous vegetation, sub-shrubs, shrubs, tall shrubs/small trees, and trees. Urban and rural settings In an urban setting landcover mapping can give useful insights into the make up of a city, such as sealed surfaces (surfaces sealed with concrete or paving for example) and urban density. The vegetation types identified as part of LandBase are suitable to accurately define the green space within a city which can be used for historical tracking, environmental assessments, and flood modelling. As much of the Leica ADS40 data stack as possible is included in the LandBase product to provide height information and local cover statistics. This information can be used for volumetric analysis and measures of building/tree density. Such information is routinely used for telecommunications network planning but may also be linked into diverse applications such as air quality models and human geography. For urban areas, Infoterra has also enhanced the LandBase classification by incorporating Lidar height information, where available. This not only improves the height precision it also helps to better define buildings into regular shaped objects. Classifying rural regions in this way opens up many new possibilities, for example woodland extent is captured in such precise detail to include individual and small groups of trees. Typically, existing wood- LandBase Level 2 classification over Ladybower Reservoir, Peak District, UK. land mapping by photo-interpretation only captures extents greater than 5’000 m². Identification of shrubs gives the possibility of hedgerow extraction and in turn an estimate of a crucial habitat. Seminatural environments, such as upland heath, have traditionally been mapped as either heather or grass dominant parcels, but can now be broken down in detail to grass, heather and bare earth components, allowing more precise extent monitoring. Using LandBase it is possible to fulfil some very specific classification goals. For example, if a local authority or council was introducing a household composting scheme or monitoring the current collection volumes, then extracting garden area would be useful information. By using growing routines within a spatially aware ruleset, garden extents have been extracted automatically for a 25 km² test site in Leicestershire. The routine includes grasses, shrubs, and trees of small extent close to buildings, while excluding woodland, recreational, and common land. A step beyond Landcover By using a similar approach of applying logical rules, a more detailed 16 class habitat map of the same study area was generated automatically to include classes such as reed bed, improved amenity grassland, and scattered scrub. Such mapping is used by local authorities for monitoring purposes but this same approach could be applied to add higher levels of landcover complexity or for detailed landuse mapping.
Garden extents extracted automatically using Land- Base and CIR imagery over Leicestershire, UK. In capturing a “snapshot in time” LandBase has been proven to aid change detection when used with historical data. Semi-automatic mapping has been carried out over Leicester and Maidstone to identify areas which have recently been built up; from new housing estates down to the level of newly tarmaced driveways. This was made possible by comparing the latest Leica ADS40 imagery and historical imagery within LandBase. Areas which have changed from vegetation to artificial surface or buildings are automatically highlighted by a classification routine. Such a method has proven even more effective than manual interpretation because of the difficulties of a seemingly easy game of spot-the-difference – we all know is never as easy as you expect. The image resolution has allowed the identification of changes to existing properties, for example building extensions, as well as new developments to be detected, and the wide area coverage has added large sample sizes giving greater statistical validity when doing cross analysis. About the Authors: Andrew Tewkesbury is Technical Development Manager at Infoterra Ltd. His focus is developing new image processing techniques and utilizing new satellite and airborne sensors. Dr Anthony Denniss, COO for Infoterra Ltd., is responsible for delivering operational efficiencies across the entire business on a dayto-day basis. Anthony’s academic background is in cartography and geological remote sensing. The Future The quality and depth of data available from the Leica ADS40 has significantly helped Infoterra meet its goal of being able to quantify and monitor the environment/surroundings in acute detail. Also the wide area collection of the sensor gives more scope for consistent data and regular updates. Statistics at a level not previously available can allow more informed decision making for a range of areas – urban planning, environmental management, and flood modelling. As the above example shows, the real power of the Leica ADS40 and successive camera’s such as the Leica ADS80, might be in providing a time series of consistent imagery, from which detailed change detection can be undertaken – allowing a new level of precision for monitoring what is really happening to our urban and rural landscapes. If you thought the Leica ADS40 only delivers good quality imagery, then think again about the wealth of information that imagery actually contains. More information: http://www.infoterra.co.uk/data_landbase.php The Global Magazine of Leica Geosystems | 21
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